Clinical characteristics of acute ischemic syndrome in China.
Bibliographic record
Abstract
OBJECTIVE: To analyse the characteristics and therapies of patients with acute ischemic syndrome in China. METHODS: This study is part of the international multicentre registry for acute ischemic syndrome. Since April 1999, the data of patients admitted to designated hospitals with acute ischemic cardiac chest pain were collected by filling in Case Report Forms offered by the Canadian Cardiovascular Collaboration. The main clinica l characteristics and in hospital events of the patients were recorded. RESULTS: Fifteen hundred and nine cases of acute ischemic syndrome from 34 hospitals nationwide were enrolled in the registry (including unstable angina and non Q-wave myocardial infarction). The mean age of the patients was 62.3. Male dominance (62.2%) was noted. The percentages of patients with chest pain at presentation and abnormal ECG were 47.8% and 89.5%, respectively. The most common clinical diagnosis on admission was unstable angina, accounting for 91.3% of the patients and non Q-wave myocardial infarction (MI), accounting for the other 8.7%. During hospitalization, the following interventions were given: thrombolytic therapy in 50 cases (3.3%), coronary angiography in 528 cases (35.0%), percutaneous transluminal coronary angioplasty (PTCA) in 253 cases (16.8%) and coronary artery bypass graft surgery (CABG) in 62 cases (4.1%). Nitrate (oral or patch ) and anti-platelet therapy were used in 1460 cases (96.8%) and 1441 cases (95.5%), respectively. The incidence of in hospital major events was 18.8%, in cluding 18 deaths (1.2%), with the most common causes being severe arrhythmias and sudden death. CONCLUSIONS: Patients with acute ischemic syndrome in China have mostly been diagnosed as cases of unstable angina. A relatively high PTCA rate but low CABG rate was noted in China. The most common cause of in hospital death is severe arrhythmias or sudden death.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".